FloodSense Manchester Project

class: center, middle, inverse, title-slide

.title[
# FloodSense Manchester Project
]
.subtitle[
## Smart Remote Flood Monitoring in Manchester
]
.author[
### CASA0023 Group Project:Chuhui ,Yingxi ,YaQi ,Aadarsh
]
.date[
### 2025/3/25 (updated: 2025-03-25)
]

---

<img src="data:image/png;base64,#pic1.png" width="97%" style="display: block; margin: auto;" />
**Mayor** of Greater Manchester Andy Burnham, speaking on BBC Radio Manchester on 2 January, said: “I think we do have to have a look back at the warnings. We were all taken by surprise to some degree. There was **no named storm**. There was **not a particular warning the authorities gave**.

The **Environment Agency** did not comment but pointed out that it has committed **£2.4 billion to invest** over the next two years to protect people from flooding, and has plans to consult on a new strategic vision for flood investment.
---
<img src="data:image/png;base64,#pic2.png" width="80%" style="display: block; margin: auto;" />
**Frequent Flood History**: Multiple significant flooding events in 1816, 1866, 1946, 1954, 1980, 2007, 2015, and 2020.

**Policy and Planning Challenges**: Policy implementation and planning coordination when managing flood risks.

**Social Vulnerability**: As the third most populous county, the area has significant social vulnerability, with low-income and marginalized communities being more susceptible to flood risks.
---

<h1 id="main-title">Flood Risk Management in Greater Manchester</h1>

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<img src="data:image/png;base64,#pic3.png" width="100%" />

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<div style="flex: 2; font-size: 16px;">
    <ol>
      <li><strong>Data Timeliness and Frequency Issues</strong>
        <ul>
          <li><strong>Problem</strong>: Satellite imagery (e.g., Landsat, Sentinel-2) has long revisit periods (8 days for Landsat 8, 5 days for Sentinel-2), delaying real-time flood monitoring.</li>
          <li><strong>Solution</strong>: Integrate high-frequency data (e.g., Sentinel-1 SAR) with drones for real-time, frequent flood monitoring.</li>
        </ul>
      </li>
      <li><strong>Cloud Interference Issues</strong>
        <ul>
          <li><strong>Problem</strong>: Optical remote sensing imagery is impacted by cloud cover, hindering data acquisition in cloudy/rainy conditions.</li>
          <li><strong>Solution</strong>: Use SAR data (e.g., Sentinel-1), unaffected by clouds, for continuous all-weather monitoring.</li>
        </ul>
      </li>
      <li><strong>Flood Warning and Emergency Response Capacity</strong>
        <ul>
          <li><strong>Problem</strong>: Complex terrain and poor infrastructure hinder accuracy and timeliness in some regions.</li>
          <li><strong>Solution</strong>: Integrate real-time data analysis and multi-source fusion (remote sensing, meteorology, sensors) to improve warning accuracy and speed.</li>
        </ul>
      </li>
    </ol>
  </div>

</div>
---

<h1 id="main-title">Flood Risk Management in Greater Manchester</h1>

<div style="display: flex; align-items: flex-start; gap: 30px;">

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<img src="data:image/png;base64,#pic4.png" width="100%" />
  </div>

<div style="flex: 2; font-size: 16px;">
    <ol>
      <li><strong>Insufficient Community Engagement and Education</strong>
        <ul>
          <li><strong>Problem</strong>: Lack of awareness and response ability to flood risks, especially in economically disadvantaged areas, despite government efforts.</li>
          <li><strong>Solution</strong>: Enhance community education and participation with flood history maps and real-time monitoring apps to boost preparedness and response.</li>
        </ul>
      </li>
      <li><strong>Limitations of Traditional Flood Control Measures</strong>
        <ul>
          <li><strong>Problem</strong>: Over-reliance on traditional engineering measures (e.g., embankments, drainage systems), facing maintenance issues and limited effectiveness.</li>
          <li><strong>Solution</strong>: Introduce nature-based solutions (e.g., wetland restoration, tree planting) alongside traditional measures to improve sustainability and reduce dependency on hard infrastructure.</li>
        </ul>
      </li>
    </ol>
  </div>

</div>
---
<div style="display: flex; height: 100vh; align-items: stretch;">

<div style="width: 55%; padding-right: 30px; box-sizing: border-box;">
    <h2 style="font-size: 24px;">Sustainable Development Goals (SDGs)</h2>
    
    <p><strong>SDG 11: Sustainable Cities and Communities</strong><br>
    Improving flood resilience directly supports SDG 11, which aims to make cities inclusive, safe, resilient, and sustainable. Flooding prevention measures align with building resilient infrastructure and ensuring access to safe public spaces.</p>
    
    <p><strong>SDG 13: Climate Action</strong><br>
    Addressing flooding contributes to climate adaptation strategies by reducing vulnerability to climate change impacts, thus fulfilling global climate action goals.</p>
    
    <p><strong>Sendai Framework for Disaster Risk Reduction</strong><br>
    Greater Manchester’s flood risk management plan aligns with the Sendai Framework, particularly in strengthening disaster risk reduction efforts and enhancing early warning systems to minimize disaster impacts.</p>
  </div>

</div>
---

# Greater Manchester
.pull-left[
- The Greater Manchester consists of 10 regions.

- These 10 regions' council together form the **Greater Manchester Combined Authority (GMCA)**

- These councils work together to solve issues in the region, transport, urban planning.

- The Greater Manchester has a total population of 2.9 million (Census, 2021)

- The region has a Gross Value Added (GVA) of 79 billion pounds which is the largest city region economy outside of London (MIDAS)  
]
  
.pull-right[

The 10 regions which form the Greater Manchester:
**Bolton, Bury, Manchester, Oldham, Rochdale, Salford, Stockport, Tameside, Trafford, and Wigan**

]

---
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## What are the factors that contribute to Flooding in the Greater Manchester area?
---
# Flooding in Greater Manchester

.pull-left[
- Greater Manchester has experienced significant flooding in recent years out of which the most disastrous one was the **2015 Boxing Day flooding**.

- Historical data suggests that rainfall is one of the **major flood trigger** factors.
  - Whether it be short-duration downpours or prolonged precipitation.

- As the region is highly urbanized, **surface water flooding risk** is also there and this will only increase in the upcoming years if not taken care of.
]

.pull-right[
<div style="text-align: center;">
  <img src="Files/flood-2025.png" alt="Flood Image" width="50%">
  <p><em>Flooded parking lot due to heavy rainfall on the last New Year's Eve in Greater Manchester (The Manc).</em></p>
</div>
]
---
- **Surface water flooding risk depends on a range of factors** (Greater Manchester Climate Change Risk Assessment, 2024):

1. Ground conditions (how waterlogged the ground is before a rainfall event)

2. The extent of impermeable surfaces

3. Drainage capacity or blocked drains

4. Topography of the land.
  
- The next important factor is **improper drainage system** due to which if the ground is saturated, then the water has nowhere to go.

- As occurred during the Boxing Day 2015 floods: Storm Eva brought prolonged, **intense rainfall on catchments that were nearly waterlogged**, causing rivers to rise rapidly and overflow.
---
# Rainfall Intensity

.pull-left[
- Heavy precipitation is the dominant meteorological factor in Greater Manchester’s flood risk.

- Cloudbursts and high-intensity rainstorms can overwhelm urban drainage, leading to flash floods.

- On 25–26 December 2015 up to 128 mm of rain fell within 36 hours in parts of the Irwell catchment north of Manchester
]

.pull-right[
<div style="text-align: center;">
  <img src="Files/rainfall-26.png" alt="Flood Image" width="80%">
  <p><em>Rainfall intensity across Greater Manchester at 8am on Boxing Day.</em></p>
</div>
]
---
# Rainfall Intensity

.pull-left[
- The river level for the River Roch on Boxing Day 2015, at its downstream meeting with the Irwell, was 1.1m higher than anything recorded in its 64-year history.

- **37 of 44** river gauges in the area recorded their highest levels.
  
- The 2019-2020 floods in the UK, were due to **cumulative rainfall** which was also then recorded as the wettest month to be recorded recently

- Climate projections (UKCP18) anticipate this pattern continuing, with warmer, **wetter winters and more intense downpours expected**.
]

.pull-left[
- Greater Manchester’s highly urbanized landscape adds another dimension to the flood problem: **impermeable surfaces and drainage capacity**.
  
  -   When heavy rain falls on cities, much of it becomes runoff.
  
- Intense rainfall, when combined with extensive paved areas and limited drainage capacity (or blocked drains), leads to dangerous accumulations of water in low-lying urban spots.

- These low lying areas with the region's old drainage system can create flood hotspots.
]

.pull-right[
<div style="text-align: center;">
  <img src="Files/surface-flooding-areas.png" alt="Flood Image" width="100%">
  <p><em>Surface water flooding hotspot areas (2024).</em></p>
</div>
]
---
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## Heavy rainfall exceeding drainage capacity is the cause of urban flash floods
---
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## Rainfall is the triggering factor and Drainage capacity is the limitation for Greater Manchester 
---
# Boxing Day 2015

.pull-left[
- 128mm of rain in 36 hours

- 37 of 44 river gauges recorded highest-ever levels

- Three river-flow gauging stations, with flows of around 1,700 m^3/s (1.7 tonnes per second)

- Approx 2000 properties flooded

- 7 Electricity Substations damaged which left 32000 properties without power.
]

.pull-left[
<div style="text-align: center;">
  <img src="Files/gm-topo.png" alt="Flood Image" width="100%">
  <p><em>Greater Manchester topography map.</em></p>
</div>
]

.pull-right[
<div style="text-align: center;">
  <img src="Files/boxingday-prop.png" alt="Flood Image" width="100%">
  <p><em>Number of Properties affected (1 km x 1 km grid).</em></p>
</div>
]
---
## Before and During the Floods
.pull-left[
- The heaviest rains from Storm Eva was experienced mostly in the North of Manchester. 
  
  - In the preceding days, **soils in these areas had become saturated and close to capacity**.
  
- The combination of prolonged average rainfall, saturated catchments, rapidly responding rivers and heavy showers on and around the 26th resulted in an **extremely rapid onset of flooding**.
]

.pull-right[
<div style="text-align: center;">
  <img src="Files/river-irwell.png" alt="Flood Image" width="100%">
  <p><em>River level (Blue line graph) Irwell and Rainfall (Blue bar graph).</em></p>
</div>
]
---
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</div>

---
# Workflow Plan

<div style="text-align: center;">
  <img src="workflow.png" style="width: 90%;">
</div>
---
#### Data Selection and Calculation of Indicators
1.Topographic Data: SRTM DEM (30m)
- Elevation (El) ; Slope (Sl); Slope Aspect (SA) ; River Distance (RD)
- Watercourse Density (WRD): Total river length / Watershed area
- Topographic Wetness Index (TWI): ln(Flow accumulation / tan(Slope))

2.Remote Sensing Data: Landsat 8 (30m)
- NDVI: (Band5 - Band4) / (Band5 + Band4)
- NDWI: (Band3 - Band5) / (Band3 + Band5)
- Land Use (LU)

3.Meteorological Data: CHIRPS (downscaled to 30m)
- Maximum 1-Day Precipitation (MIDP): maximum daily precipitation for 40 days between historical flood events

4.Pedological Data: Harmonized World Soil Database (downscaled to 30m)
- Soil Texture (ST): 1-8 (sand → clay)

---
#### Random Forest Modelling
<div style="text-align: center;">
  <img src="RF modeling.png" style="width: 90%;">
</div>
---
<div style="display: flex; height: 100vh; align-items: stretch;">

<div style="width: 50%; padding-right: 20px; box-sizing: border-box;">
    <h3 style="font-size: 24px;">Visual Risk Mapping</h3>
    <ul>
      <li><strong>Map Display:</strong><br>
          Base map(Mapbox)+risk layer overlay<br>
          click-to-query risk values and detailed indicators for any location
      </li>
    </ul>
    <img src="p3d52.png" style="height: 250px; margin-top: 10px;">
    <div style="font-size: 16px; color: #666; margin-top: 10px; text-align: left;">
      Source: Farhadi and Najafzadeh, 2021
    </div>
  </div>

<div style="width: 50%; display: flex; justify-content: center; align-items: center;">
    <img src="p3d5.png" style="max-height: 100vh; max-width: 80%; object-fit: contain;">
  </div>

</div>

---
### Sample Dashboard Preview -- functional modules

<div style="text-align: center;">
  <img src="交互式设计.png" style="width: 90%;">
  <div style="font-size: 16px; color: #666; margin-top: 10px; text-align: center;">
      Source: global_flood_mapper Lab, 2023
    </div>
</div>

---
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<body>

<h1 id="main-title">Time-line layout</h1>

<div class="timeline-layout">
 
  
  <div class="left-tabs">
   <div class="tab active" onclick="showPhase(0)">
      PHASE 1<br>
      <span class="phase-sub">Months 1–3</span>
    </div>
    <div class="tab" onclick="showPhase(1)">
      PHASE 2<br>
      <span class="phase-sub">Months 4–6</span>
    </div>
    <div class="tab" onclick="showPhase(2)">
      PHASE 3<br>
      <span class="phase-sub">Months 7–9</span>
    </div>
    <div class="tab" onclick="showPhase(3)">
      PHASE 4<br>
      <span class="phase-sub">Months 10–12</span>
    </div>
  </div>

<div class="content-container">

<div class="phase-content active" id="phase-0">
      <div class="month-section">
        <div class="month-title">January (Month 1)</div>
        <div class="section-block">
          <div class="section-title">Planning:</div>
          <p>• Conduct project kickoff meeting with key stakeholders<br>
             • Clarify goals for flood risk management</p>
        </div>
        <div class="section-block">
          <div class="section-title">Execution:</div>
          <p>• Gather historical flood records<br>
             • Collect geographic boundary data</p>
        </div>
        <div class="section-block">
          <div class="section-title">Evaluation:</div>
          <p>• Initial feasibility check<br>
             • Identify budget constraints</p>
        </div>
      </div>
      
    </div>

<div class="phase-content" id="phase-1">
      <div class="month-section">
        <div class="month-title">April (Month 4)</div>
        <div class="section-block">
          <div class="section-title">Planning:</div>
          <p>• Define tasks for next quarter<br>
             • Resource allocation</p>
        </div>
        <div class="section-block">
          <div class="section-title">Execution:</div>
          <p>• Develop GEE scripts<br>
             • Data cleaning</p>
        </div>
        <div class="section-block">
          <div class="section-title">Evaluation:</div>
          <p>• Check script outputs<br>
             • Document initial findings</p>
        </div>
      </div>
      
    </div>

<div class="phase-content" id="phase-2">
      <div class="month-section">
        <div class="month-title">July (Month 7)</div>
        <div class="section-block">
          <div class="section-title">Planning:</div>
          <p>• Setup NDVI analysis pipeline<br>
             • Confirm study area expansions</p>
        </div>
        <div class="section-block">
          <div class="section-title">Execution:</div>
          <p>• Run NDVI scripts<br>
             • Collect NDVI results for test region</p>
        </div>
        <div class="section-block">
          <div class="section-title">Evaluation:</div>
          <p>• Validate NDVI data<br>
             • Adjust thresholds as needed</p>
        </div>
      </div>
      
    </div>

<div class="phase-content" id="phase-3">
      <div class="month-section">
        <div class="month-title">October (Month 10)</div>
        <div class="section-block">
          <div class="section-title">Planning:</div>
          <p>• Prepare pilot test scenario<br>
             • Finalize deliverables timeline</p>
        </div>
        <div class="section-block">
          <div class="section-title">Execution:</div>
          <p>• Pilot test and gather feedback<br>
             • Address issues found in pilot</p>
        </div>
        <div class="section-block">
          <div class="section-title">Evaluation:</div>
          <p>• Final review<br>
             • Project delivery & sign-off</p>
        </div>
      </div>
      
    </div>

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      <img id="phase-image" src="1.png" alt="Project Phase Visualization">
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     font-family: 'Times New Roman'; font-size: 48px; color:#003366; 
     transform: rotate(-15deg);">
  TIMELINE LAYOUT
</div>

---

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      </div>
      <h1 style="color:#003366; margin:0; font-family: 'Times New Roman', serif; 
          font-size: 36px; font-weight: 600; letter-spacing: -0.5px;">
        Strategic Budget Allocation
      </h1>
    </div>

<div style="border-left: 3px solid #0083FF; padding-left: 20px; margin-left: 60px;">
      <p style="color:#4A5568; font-size: 20px; line-height: 1.4; margin:0 0 15px 0;
         font-family: 'Georgia', serif;">
        Multi-year investment strategy across core capabilities<br>
        <span style="color:#718096; font-size: 16px;">(FY Implementation Roadmap)</span>
      </p>
    </div>
  </div>

<div class="phase-content active">
    <h3>Key Investment Areas</h3>
     <ul>
      <li>Infrastructure Modernization (35%)</li>
      <li>R&D Innovation Fund (28%)</li>
      <li>Operational Excellence (22%)</li>
      <li>Talent Development (15%)</li>
    </ul>
  </div>

</div>

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    STRATEGIC FINANCE
  </div>

</div>
---
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![](data:image/png;base64,#budgetmap.png)

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">
  Thank You
</h1>

---
# References list
Greater Manchester Combined Authority. Who we are. Available at: https://www.greatermanchester-ca.gov.uk/who-we-are/

About Manchester. Boxing Day floods were the worst ever. Available at: https://aboutmanchester.co.uk/boxing-day-floods-were-the-worst-ever/

World Bank (2022). Manchester case study. Available at: https://thedocs.worldbank.org/en/doc/67e70f6cb8dba18f836791e68faa0ac8-0070012022/original/F-Manchester-Case-Study.pdf

Greater Manchester Combined Authority. Greater Manchester Climate Change Risk Assessment Report. Available at: https://www.greatermanchester-ca.gov.uk/media/qtrhgi2y/gm-ccra-report_final.pdf

---
Greater Manchester Combined Authority. Greater Manchester 5-year environment plan. Available at: https://www.greatermanchester-ca.gov.uk/media/alnl0fsy/gmca_5-year-plan_final_digital_v3-ua.pdf

Greater Manchester Combined Authority. Greater Manchester Strategy. Available at: https://www.greatermanchester-ca.gov.uk/what-we-do/greater-manchester-strategy/

Greater Manchester Combined Authority (2022). Corporate Plan 2022–2025. Available at: https://www.greatermanchester-ca.gov.uk/media/6734/corporate-plan-2022-2025.pdf

Harrigan, S., Prudhomme, C., Parry, S., Smith, K. and Tanguy, M. (2021). The 2019/2020 floods in the UK: A hydrological appraisal. Hydrology Research, 52(3), pp. 686–704. Available at: https://www.researchgate.net/publication/351377240_The_20192020_floods_in_the_UK_a_hydrological_appraisal

Invest in Manchester. Our economy. Available at: https://www.investinmanchester.com/why-manchester/our-economy/

Real-Time Flood Monitoring Based on Multi-Sensor Optical Imagery and Machine Learning
Farhadi, H., Ebadi, H., Kiani, A., & Asgary, A. (2024). Near real-time flood monitoring using multi-sensor optical imagery and machine learning by GEE: An automatic feature-based multi-class classification approach. Remote Sensing, 16(23), 4454.

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